摘要
电渣重熔过程中需要兼顾产品质量、生产效率、生产成本等因素,本文以熔铸电流、冷却水流量、渣池深度作为输入变量,以电极端部锥高、熔化效率、电功率因数作为输出变量,利用BP人工神经网络理论,在MatLab平台上建立起电渣重熔生产工艺优化模型。实验证明,该模型可以用于电渣重熔过程中工艺参数的辅助选择。
In ESR process,product quality,production efficiency,production costs and other factors needs to be taken into account balanced.In this research,an optimization model of ESR product process was established in the MatLab platform using BP neural network theory.The model using the melting current,cooling water flow,slag pool depth as input variables,and using cone-height of the electrode bottom,melting rate,electric power factor as the output variable.Experiments show that the model can be used for the parameters choice auxiliary in ESR product process.
出处
《铸造技术》
CAS
北大核心
2010年第10期1291-1293,共3页
Foundry Technology
基金
国家863计划资助项目(715-009-0110)
南昌市科技局资助项目
